1. Field of Invention
The invention relates to a method for determining image output types and, in particular, to a method for determining image output types that uses the analysis of path conditions satisfied by each consecutive two pixels in the image to perform photo/text separation.
2. Related Art
Image outputs usually include photo, text, and photo-text mixed cases. Including the possibility of black-and-white (BW) and color image, the image output combinations become rather complicated. In order for an image output device (such as inkjet printers and laser printers) to have good output speed and quality, performing efficient photo/text separation is a key technique.
To achieve this goal, the image output device often executes a so-called photo/text separation procedure before actual output. The main purpose of this step is to output the photo and text parts of the image in different methods, so that both the photo and text parts can have the optimized image output quality. Of course, saving the ink is also another advantage of the photo/text separation procedure.
The main difference between the photo and text image output is whether the halftone process is involved. Since photos have non-continuous tones, it is more suitable to be processed using the halftone process. On the other hand, the text has a continuous tone and therefore is not suitable for the halftone process. If no photo/text separation procedure is done before the image output, both of them are processed and output through the halftone process. This greatly affects the quality of the output images. Moreover, using the halftone process for the text part wastes a lot of printing materials.
Therefore, executing a photo/text separation procedure before image output is necessary. There are many photo/text separation techniques introduced in the prior art. Their main technical means is to perform statistical analyses in individual characteristic values of all the pixels in the original image. They totally ignore the existence of possible correlation between consecutive pixels. Therefore, it is likely to have larger errors in the photo/text separation.
Moreover, the photo/text separation performed by the conventional methods often has to perform an operation, determination, recording, and statistical analysis for each of the pixels. Thus, their efficiency is not satisfactory. In particular, if the original image is larger in size, computing for each pixel will affect the overall operation efficiency. This is another drawback of the prior art.
Consequently, it is imperative to provide a new method that is not likely to make errors in the photo/text separation while at the same time can have better operation efficiency.